It's amazing to think that R (or S) had data frames since the 70s and only now are other languages implementing them. There are some quirks of course, and pandas introduced some convenient features. But the R community has also provided its own improvements in the way of data.table, and now, dplyr.
Re:Dataframes – Julia, R, Python
by ajinkyakale on Wednesday December 24, 2014 @10:30PM
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Data.table package by matt dowle definitely deserves a mention! Its fast and I like the indexing functonalities it provides. The benchmark timings are pretty impressive.
Re:Dataframes – Julia, R, Python
by arun_sriniv on Tuesday December 30, 2014 @06:21AM
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@ajinkyakale, thanks. What'd be also interesting is to benchmark memory usage in addition to runtime.
Re:Dataframes – Julia, R, Python
by ajinkyakale on Tuesday December 30, 2014 @11:55PM
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I should have mentioned you (arun_sriniv) as the co-developer of data.table! Thanks for all the hard work.
And yes, memory usage will be interesting as that is the bottleneck when it comes to large dataset. I am working on something on those lines. Will post something soon :)
Re:Dataframes – Julia, R, Python
by arun_sriniv on Wednesday December 31, 2014 @04:32AM
(#8818722)
No worries :-). And glad to hear you're working on it! Let me know if I can be of any help.
R also stands out because it is so easy to run a wide variety of statistical methods easily on a data frame.